We detail how confidential federated analytics technology is leveraged to understand on-device generative AI features, ensuring strong transparency in user data handling and analysis. Generative AI (GenAI) enables personalized experiences and powers the creation of unstructured data, including summaries, transcriptions, and more. Insights into real-world AI use [1, 2] can help GenAI developers enhance their tools […]
Project Suncatcher is a moonshot exploring a new frontier: equipping solar-powered satellite constellations with TPUs and free-space optical links to one day scale machine learning compute in space. Artificial intelligence (AI) is a foundational technology that could reshape our world, driving new scientific discoveries and helping us tackle humanity’s greatest challenges. Now, we’re asking where
Exploring a space-based, scalable AI infrastructure system design Read More »
We introduce the first deep learning–powered benchmark for proactive deforestation risk forecasting. Nature underpins our climate, our economies, and our very lives. And within nature, forests stand as one of the most powerful pillars — storing carbon, regulating rainfall, mitigating floods, and harboring the majority of the planet’s terrestrial biodiversity. Yet, despite their critical importance, the world
Forecasting the future of forests with AI: From counting losses to predicting risk Read More »
DS-STAR is a state-of-the-art data science agent whose versatility is shown by its ability to automate a range of tasks — from statistical analysis to visualization and data wrangling — across various data types, culminating in a top-ranking performance on the famous DABStep benchmark. Data science is a field dedicated to transforming raw data into
DS-STAR: A state-of-the-art versatile data science agent Read More »
We introduce Nested Learning, a new approach to machine learning that views models as a set of smaller, nested optimization problems, each with its own internal workflow, in order to mitigate or even completely avoid the issue of “catastrophic forgetting”, where learning new tasks sacrifices proficiency on old tasks. The last decade has seen incredible
Introducing Nested Learning: A new ML paradigm for continual learning Read More »
We announce the release of JAX-Privacy 1.0, a library for differentially private machine learning on the high-performance computing library, JAX. From personalized recommendations to scientific advances, AI models are helping to improve lives and transform industries. But the impact and accuracy of these AI models is often determined by the quality of data they use.
Differentially private machine learning at scale with JAX-Privacy Read More »
New theoretical work from Google Quantum AI shows that large scale quantum computers could solve certain optimization problems that are intractable for conventional classical computers. From designing more efficient airline routes to organizing clinical trials, optimization problems are everywhere. Yet for many real-world challenges, even our most powerful supercomputers struggle to find the best solution.
Natural Forests of the World 2020 is an AI-powered map that distinguishes natural forests from other tree cover. This critical baseline helps governments, companies, and communities meet deforestation-free goals and protect ecosystems. Forests are vital for our planet as they regulate rainfall, mitigate floods, store and sequester carbon, and help sustain the majority of the planet’s
We introduce a novel implementation of generative UI, enabling AI models to create immersive experiences and interactive tools and simulations, all generated completely on the fly for any prompt. This is now rolling out in the Gemini app and Google Search, starting with AI Mode. Generative UI is a powerful capability in which an AI
Generative UI: A rich, custom, visual interactive user experience for any prompt Read More »
